ISNN
2005
Springer
14 years 6 months ago
2005
Springer
Abstract. The present study investigates a geometrical method for optimizing the kernel function of a support vector machine. The method is an improvement of the one proposed in [4...
GECCO
2005
Springer
14 years 6 months ago
2005
Springer
In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suit...
AIIA
2005
Springer
14 years 6 months ago
2005
Springer
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, th...
KES
2007
Springer
2007
Springer
Inductive Concept Retrieval and Query Answering with Semantic Knowledge Bases Through Kernel Methods
14 years 6 months ago
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
IJCNN
2007
IEEE
14 years 6 months ago
2007
IEEE
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
In this paper, a method to generalize previously proposed Chebyshev Kernel function is presented for Support Vector Classification in order to obtain more robust and higher classi...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Registration of 3D surfaces is a critical step for shape analysis. Recent studies show that spectral representations based on intrinsic pairwise geodesic distances between points ...
ICML
2005
IEEE
15 years 1 months ago
2005
IEEE
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
ICML
2006
IEEE
15 years 1 months ago
2006
IEEE
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
ICML
2007
IEEE
15 years 1 months ago
2007
IEEE
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...